rycolab / differentiable-subset-pruning

Related projects: ⓘ

• Noahs-ARK / RFA
  ☆32Updated 3 years ago
• ptlmasking / maskbert
  ☆20Updated 3 years ago
• microsoft / Stochastic-Mixture-of-Experts
  This package implements THOR: Transformer with Stochastic Experts.
  ☆60Updated 2 years ago
• Shark-NLP / CAB
  ☆28Updated last year
• dguo98 / DiffPruning
  Parameter Efficient Transfer Learning with Diff Pruning
  ☆70Updated 3 years ago
• QingruZhang / PLATON
  This pytorch package implements PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance (ICML 2022).
  ☆39Updated last year
• princeton-nlp / LM-Kernel-FT
  A Kernel-Based View of Language Model Fine-Tuning https://arxiv.org/abs/2210.05643
  ☆68Updated last year
• Hunter-DDM / stablemoe
  Code for the ACL-2022 paper "StableMoE: Stable Routing Strategy for Mixture of Experts"
  ☆41Updated 2 years ago
• varunnair18 / FISH
  Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).
  ☆54Updated 2 years ago
• asappresearch / flop
  Pytorch library for factorized L0-based pruning.
  ☆42Updated 11 months ago
• pkuzengqi / Skyformer
  Skyformer: Remodel Self-Attention with Gaussian Kernel and Nystr\"om Method (NeurIPS 2021)
  ☆58Updated 2 years ago
• huggingface / block_movement_pruning
  Block Sparse movement pruning
  ☆77Updated 3 years ago
• VITA-Group / BERT-Tickets
  [NeurIPS 2020] "The Lottery Ticket Hypothesis for Pre-trained BERT Networks", Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Ya…
  ☆137Updated 2 years ago
• VITA-Group / Random-MoE-as-Dropout
  [ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal…
  ☆42Updated last year
• rabeehk / vibert
  Implementation for Variational Information Bottleneck for Effective Low-resource Fine-tuning, ICLR 2021
  ☆36Updated 3 years ago
• kernelmachine / demix
  DEMix Layers for Modular Language Modeling
  ☆51Updated 3 years ago
• cliang1453 / SAGE
  No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models (ICLR 2022)
  ☆29Updated 2 years ago
• IBM / PoWER-BERT
  Method to improve inference time for BERT. This is an implementation of the paper titled "PoWER-BERT: Accelerating BERT Inference via Pro…
  ☆58Updated last year
• facebookresearch / ELECTRA-Fewshot-Learning
  This repository contains the code for paper Prompting ELECTRA Few-Shot Learning with Discriminative Pre-Trained Models.
  ☆45Updated 2 years ago
• VITA-Group / EarlyBERT
  [ACL-IJCNLP 2021] "EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets" by Xiaohan Chen, Yu Cheng, Shuohang Wang, Zhe Gan, …
  ☆17Updated 2 years ago
• kssteven418 / LTP
  [KDD'22] Learned Token Pruning for Transformers
  ☆91Updated last year
• sai-prasanna / bert-experiments
  ☆20Updated 3 years ago
• microsoft / SparseMixer
  Sparse Backpropagation for Mixture-of-Expert Training
  ☆17Updated 2 months ago
• jxhe / efficient-knnlm
  Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)
  ☆71Updated 2 years ago
• raymin0223 / fast_robust_early_exit
  Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding (EMNLP 2023 Long)
  ☆51Updated 3 months ago
• GeneZC / MiniMoE
  Code for ACL 2023 paper titled "Lifting the Curse of Capacity Gap in Distilling Language Models"
  ☆28Updated last year
• amodaresi / AdapLeR
  ☆22Updated last year
• cambridgeltl / autopeft
  AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning (Zhou et al.; TACL)
  ☆42Updated 6 months ago
• ghazi-f / QKVAE
  Implementation of QKVAE
  ☆11Updated last year
• castorini / berxit
  ☆21Updated 3 years ago